As data collection, processing and communication tools become more available, their use in practical applications becomes more desirable. As one example, data collection, processing and communication regarding environmental conditions can have significant beneficial applications. There are a number of environmental conditions that can be of concern and subject of detection at both localized and regional levels. For example, a need always exists for more accurate, real-time data collection which permits detection of traffic patterns, including automotive patterns, train patterns and other vehicular patterns on roads, bridges, tunnels and so forth. Further, a need always exists for more accurate, real-time data collection which permits detection of weather patterns, including hurricane patterns, tornado patterns and other forces of nature such as earthquakes. Still further, data collection which permits the predictive analysis of such patterns and occurrences is of even greater value. For example, the predictive analysis of a storm path based upon the data collections can be used to provide better advanced warning to people in a storm or flood path.
Such data collection and analysis would typically require a broad distribution of collection points to perform quickly and accurately. However, implementing and maintaining such a distribution of collection points solely for the purpose of data collection regarding traffic patterns, weather patterns and other forces of nature would become cost prohibitive. Further, the distribution of such devices would require implementation and maintenance of communication elements between the devices to exchange data quickly and accurately, which further becomes cost prohibitive.